Wrap-up

Analyzing Survey Data in R

Kelly McConville

Assistant Professor of Statistics

R packages

  • survey: To analyze survey data
  • dplyr: To wrangle data
  • ggplot2: To graph the data
Analyzing Survey Data in R

Course summary

 

  • Ch 1: Survey fundamentals
    • Common design features: clustering, stratification
    • Survey weights
    • Telling R about your svydesign()
  • Ch 2: Categorical data
    • Frequency and contingency tables with svytable()
    • Bar graphs with geom_col()
    • Inference with svychisq()
Analyzing Survey Data in R

Course summary

  • Ch 3: Quantitative and categorical data
    • Summary stats with svymean(), svytotal(), svyquantile()
    • Domain estimates with svyby()
    • Describing shape with geom_histogram(), geom_density()
    • Inference with svyttest()
  • Ch 4: Modeling trends
    • Mapping survey weights in geom_point()
    • Linear trends with geom_smooth(method = "lm")
    • Linear regression with svyglm()
Analyzing Survey Data in R

Extensions

  • Estimating more complex population quantities.
    • EX: svyratio()
  • Building more complex models
    • EX : svyglm(Diabetes ~ Age, design = NHANES_design, family = quasibinomial)
Analyzing Survey Data in R

Congratulations!

Analyzing Survey Data in R

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